Localization for indoor applications can be a challenging task if global positioning systems (GPS) are not available. There have been several attempts to achieve location estimation using wireless signals (for example, using IEEE 802.11 signals). The existing methods, however, mostly target cellphone applications and there has not been a focus, for example, on the localization of mobile routers in wireless mesh networks. However, the localization of mobile routers is particularly important since many applications of wireless mesh networks involve deployments in regions where GPS signals may not be available, such as underground mines and inside plants.
There have been several efforts to obtain location information in the absence of GPS data and in particular for indoor applications. Among them are navigation methods based on acoustic, optical, magnetic and electromagnetic waves. Applications involving wireless communication may leverage the information obtained through propagation of wireless signals for localization purposes. There are several methods of doing this, most notably geometric- and fingerprinting-based methods. The geometric methods use propagation properties of received wireless signals, and therefore, these are significantly dependent on the accuracy of a channel model of the transmission of the wireless signals. On the other hand, the fingerprinting-based approach merely relies on the signal signatures measured at each point and hence, is immune to the shortcomings induced by the inaccuracies of channel modeling.
It is desirable to have methods, systems and apparatuses for localization utilizing fingerprinting of the received wireless signal within a wireless mesh network.